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Published on: February 23, 2024
Understanding Artificial Intelligence in Dental Nursing: An Online Survey on Familiarity, Attitudes, and Expectations
Yi-Fu Yu1, Lei-Ming Cao1, Huan Sun1
1State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, Hubei, China.
Abstract:
To explore dental nurses' expectations and identify key factors influencing their familiarity, attitudes, and expectations regarding artificial intelligence, an anonymous online survey was conducted using a structured 23-item questionnaire, following Checklist for Reporting Results of Internet E-Surveys (CHERRIES) guidelines. Recruitment utilized purposive and snowball sampling methods, targeting nurses from diverse departments across public and private institutions. Statistical analyses, including χ 2 tests and generalized estimating equations, were used to explore associations between demographics, familiarity, and attitudes toward artificial intelligence. Questionnaires were collected from 14 different dental departments, including 5 public hospitals and 5 private stomatological clinics. A total of 816 valid responses were analyzed. Most respondents (68.9%) had limited exposure to artificial intelligence-based nursing tools. Familiarity with artificial intelligence was significantly associated with experience in artificial intelligence-related projects and work in specialized departments such as outpatient clinics. Although nurses acknowledged high costs and complexity as barriers, over 56.7% expressed a willingness to adopt artificial intelligence technologies, reflecting optimism about its future in nursing. Despite limited familiarity and accessibility, nurses demonstrate a positive attitude toward artificial intelligence applications. Addressing barriers such as cost, training, and usability will be critical to fostering broader adoption.
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